mirrors/django
1
0
Fork 0
mirror of https://github.com/django/django.git synced 2024-11-18 07:26:04 +00:00
Code Issues 24 Releases Wiki Activity
a394289b58
django/docs/ref/models/database-functions.txt

1622 lines
52 KiB
Plaintext
Raw Blame History

==================
Database Functions
==================
.. module:: django.db.models.functions
:synopsis: Database Functions
The classes documented below provide a way for users to use functions provided
by the underlying database as annotations, aggregations, or filters in Django.
Functions are also :doc:`expressions <expressions>`, so they can be used and
combined with other expressions like :ref:`aggregate functions
<aggregation-functions>`.
We'll be using the following model in examples of each function::
class Author(models.Model):
name = models.CharField(max_length=50)
age = models.PositiveIntegerField(null=True, blank=True)
alias = models.CharField(max_length=50, null=True, blank=True)
goes_by = models.CharField(max_length=50, null=True, blank=True)
We don't usually recommend allowing ``null=True`` for ``CharField`` since this
allows the field to have two "empty values", but it's important for the
``Coalesce`` example below.
.. _comparison-functions:
Comparison and conversion functions
===================================
``Cast``
--------
.. class:: Cast(expression, output_field)
Forces the result type of ``expression`` to be the one from ``output_field``.
Usage example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Cast
>>> Value.objects.create(integer=4)
>>> value = Value.objects.annotate(as_float=Cast('integer', FloatField())).get()
>>> print(value.as_float)
4.0
``Coalesce``
------------
.. class:: Coalesce(*expressions, **extra)
Accepts a list of at least two field names or expressions and returns the
first non-null value (note that an empty string is not considered a null
value). Each argument must be of a similar type, so mixing text and numbers
will result in a database error.
Usage examples::
>>> # Get a screen name from least to most public
>>> from django.db.models import Sum, Value as V
>>> from django.db.models.functions import Coalesce
>>> Author.objects.create(name='Margaret Smith', goes_by='Maggie')
>>> author = Author.objects.annotate(
... screen_name=Coalesce('alias', 'goes_by', 'name')).get()
>>> print(author.screen_name)
Maggie
>>> # Prevent an aggregate Sum() from returning None
>>> aggregated = Author.objects.aggregate(
... combined_age=Coalesce(Sum('age'), V(0)),
... combined_age_default=Sum('age'))
>>> print(aggregated['combined_age'])
0
>>> print(aggregated['combined_age_default'])
None
.. warning::
A Python value passed to ``Coalesce`` on MySQL may be converted to an
incorrect type unless explicitly cast to the correct database type:
>>> from django.db.models import DateTimeField
>>> from django.db.models.functions import Cast, Coalesce
>>> from django.utils import timezone
>>> now = timezone.now()
>>> Coalesce('updated', Cast(now, DateTimeField()))
``Greatest``
------------
.. class:: Greatest(*expressions, **extra)
Accepts a list of at least two field names or expressions and returns the
greatest value. Each argument must be of a similar type, so mixing text and
numbers will result in a database error.
Usage example::
class Blog(models.Model):
body = models.TextField()
modified = models.DateTimeField(auto_now=True)
class Comment(models.Model):
body = models.TextField()
modified = models.DateTimeField(auto_now=True)
blog = models.ForeignKey(Blog, on_delete=models.CASCADE)
>>> from django.db.models.functions import Greatest
>>> blog = Blog.objects.create(body='Greatest is the best.')
>>> comment = Comment.objects.create(body='No, Least is better.', blog=blog)
>>> comments = Comment.objects.annotate(last_updated=Greatest('modified', 'blog__modified'))
>>> annotated_comment = comments.get()
``annotated_comment.last_updated`` will be the most recent of ``blog.modified``
and ``comment.modified``.
.. warning::
The behavior of ``Greatest`` when one or more expression may be ``null``
varies between databases:
- PostgreSQL: ``Greatest`` will return the largest non-null expression,
or ``null`` if all expressions are ``null``.
- SQLite, Oracle, and MySQL: If any expression is ``null``, ``Greatest``
will return ``null``.
The PostgreSQL behavior can be emulated using ``Coalesce`` if you know
a sensible minimum value to provide as a default.
``Least``
---------
.. class:: Least(*expressions, **extra)
Accepts a list of at least two field names or expressions and returns the
least value. Each argument must be of a similar type, so mixing text and numbers
will result in a database error.
.. warning::
The behavior of ``Least`` when one or more expression may be ``null``
varies between databases:
- PostgreSQL: ``Least`` will return the smallest non-null expression,
or ``null`` if all expressions are ``null``.
- SQLite, Oracle, and MySQL: If any expression is ``null``, ``Least``
will return ``null``.
The PostgreSQL behavior can be emulated using ``Coalesce`` if you know
a sensible maximum value to provide as a default.
.. _date-functions:
Date functions
==============
We'll be using the following model in examples of each function::
class Experiment(models.Model):
start_datetime = models.DateTimeField()
start_date = models.DateField(null=True, blank=True)
start_time = models.TimeField(null=True, blank=True)
end_datetime = models.DateTimeField(null=True, blank=True)
end_date = models.DateField(null=True, blank=True)
end_time = models.TimeField(null=True, blank=True)
``Extract``
-----------
.. class:: Extract(expression, lookup_name=None, tzinfo=None, **extra)
Extracts a component of a date as a number.
Takes an ``expression`` representing a ``DateField``, ``DateTimeField``,
``TimeField``, or ``DurationField`` and a ``lookup_name``, and returns the part
of the date referenced by ``lookup_name`` as an ``IntegerField``.
Django usually uses the databases' extract function, so you may use any
``lookup_name`` that your database supports. A ``tzinfo`` subclass, usually
provided by ``pytz``, can be passed to extract a value in a specific timezone.
Given the datetime ``2015-06-15 23:30:01.000321+00:00``, the built-in
``lookup_name``\s return:
* "year": 2015
* "iso_year": 2015
* "quarter": 2
* "month": 6
* "day": 15
* "week": 25
* "week_day": 2
* "hour": 23
* "minute": 30
* "second": 1
If a different timezone like ``Australia/Melbourne`` is active in Django, then
the datetime is converted to the timezone before the value is extracted. The
timezone offset for Melbourne in the example date above is +10:00. The values
returned when this timezone is active will be the same as above except for:
* "day": 16
* "week_day": 3
* "hour": 9
.. admonition:: ``week_day`` values
The ``week_day`` ``lookup_type`` is calculated differently from most
databases and from Python's standard functions. This function will return
``1`` for Sunday, ``2`` for Monday, through ``7`` for Saturday.
The equivalent calculation in Python is::
>>> from datetime import datetime
>>> dt = datetime(2015, 6, 15)
>>> (dt.isoweekday() % 7) + 1
2
.. admonition:: ``week`` values
The ``week`` ``lookup_type`` is calculated based on `ISO-8601
<https://en.wikipedia.org/wiki/ISO-8601>`_, i.e.,
a week starts on a Monday. The first week of a year is the one that
contains the year's first Thursday, i.e. the first week has the majority
(four or more) of its days in the year. The value returned is in the range
1 to 52 or 53.
Each ``lookup_name`` above has a corresponding ``Extract`` subclass (listed
below) that should typically be used instead of the more verbose equivalent,
e.g. use ``ExtractYear(...)`` rather than ``Extract(..., lookup_name='year')``.
Usage example::
>>> from datetime import datetime
>>> from django.db.models.functions import Extract
>>> start = datetime(2015, 6, 15)
>>> end = datetime(2015, 7, 2)
>>> Experiment.objects.create(
... start_datetime=start, start_date=start.date(),
... end_datetime=end, end_date=end.date())
>>> # Add the experiment start year as a field in the QuerySet.
>>> experiment = Experiment.objects.annotate(
... start_year=Extract('start_datetime', 'year')).get()
>>> experiment.start_year
2015
>>> # How many experiments completed in the same year in which they started?
>>> Experiment.objects.filter(
... start_datetime__year=Extract('end_datetime', 'year')).count()
1
``DateField`` extracts
~~~~~~~~~~~~~~~~~~~~~~
.. class:: ExtractYear(expression, tzinfo=None, **extra)
.. attribute:: lookup_name = 'year'
.. class:: ExtractIsoYear(expression, tzinfo=None, **extra)
.. versionadded:: 2.2
Returns the ISO-8601 week-numbering year.
.. attribute:: lookup_name = 'iso_year'
.. class:: ExtractMonth(expression, tzinfo=None, **extra)
.. attribute:: lookup_name = 'month'
.. class:: ExtractDay(expression, tzinfo=None, **extra)
.. attribute:: lookup_name = 'day'
.. class:: ExtractWeekDay(expression, tzinfo=None, **extra)
.. attribute:: lookup_name = 'week_day'
.. class:: ExtractWeek(expression, tzinfo=None, **extra)
.. attribute:: lookup_name = 'week'
.. class:: ExtractQuarter(expression, tzinfo=None, **extra)
.. attribute:: lookup_name = 'quarter'
These are logically equivalent to ``Extract('date_field', lookup_name)``. Each
class is also a ``Transform`` registered on ``DateField`` and ``DateTimeField``
as ``__(lookup_name)``, e.g. ``__year``.
Since ``DateField``\s don't have a time component, only ``Extract`` subclasses
that deal with date-parts can be used with ``DateField``::
>>> from datetime import datetime
>>> from django.utils import timezone
>>> from django.db.models.functions import (
... ExtractDay, ExtractMonth, ExtractQuarter, ExtractWeek,
... ExtractWeekDay, ExtractIsoYear, ExtractYear,
... )
>>> start_2015 = datetime(2015, 6, 15, 23, 30, 1, tzinfo=timezone.utc)
>>> end_2015 = datetime(2015, 6, 16, 13, 11, 27, tzinfo=timezone.utc)
>>> Experiment.objects.create(
... start_datetime=start_2015, start_date=start_2015.date(),
... end_datetime=end_2015, end_date=end_2015.date())
>>> Experiment.objects.annotate(
... year=ExtractYear('start_date'),
... isoyear=ExtractIsoYear('start_date'),
... quarter=ExtractQuarter('start_date'),
... month=ExtractMonth('start_date'),
... week=ExtractWeek('start_date'),
... day=ExtractDay('start_date'),
... weekday=ExtractWeekDay('start_date'),
... ).values('year', 'isoyear', 'quarter', 'month', 'week', 'day', 'weekday').get(
... end_date__year=ExtractYear('start_date'),
... )
{'year': 2015, 'isoyear': 2015, 'quarter': 2, 'month': 6, 'week': 25,
'day': 15, 'weekday': 2}
``DateTimeField`` extracts
~~~~~~~~~~~~~~~~~~~~~~~~~~
In addition to the following, all extracts for ``DateField`` listed above may
also be used on ``DateTimeField``\s .
.. class:: ExtractHour(expression, tzinfo=None, **extra)
.. attribute:: lookup_name = 'hour'
.. class:: ExtractMinute(expression, tzinfo=None, **extra)
.. attribute:: lookup_name = 'minute'
.. class:: ExtractSecond(expression, tzinfo=None, **extra)
.. attribute:: lookup_name = 'second'
These are logically equivalent to ``Extract('datetime_field', lookup_name)``.
Each class is also a ``Transform`` registered on ``DateTimeField`` as
``__(lookup_name)``, e.g. ``__minute``.
``DateTimeField`` examples::
>>> from datetime import datetime
>>> from django.utils import timezone
>>> from django.db.models.functions import (
... ExtractDay, ExtractHour, ExtractMinute, ExtractMonth,
... ExtractQuarter, ExtractSecond, ExtractWeek, ExtractWeekDay,
... ExtractYear,
... )
>>> start_2015 = datetime(2015, 6, 15, 23, 30, 1, tzinfo=timezone.utc)
>>> end_2015 = datetime(2015, 6, 16, 13, 11, 27, tzinfo=timezone.utc)
>>> Experiment.objects.create(
... start_datetime=start_2015, start_date=start_2015.date(),
... end_datetime=end_2015, end_date=end_2015.date())
>>> Experiment.objects.annotate(
... year=ExtractYear('start_datetime'),
... isoyear=ExtractIsoYear('start_datetime'),
... quarter=ExtractQuarter('start_datetime'),
... month=ExtractMonth('start_datetime'),
... week=ExtractWeek('start_datetime'),
... day=ExtractDay('start_datetime'),
... weekday=ExtractWeekDay('start_datetime'),
... hour=ExtractHour('start_datetime'),
... minute=ExtractMinute('start_datetime'),
... second=ExtractSecond('start_datetime'),
... ).values(
... 'year', 'isoyear', 'month', 'week', 'day',
... 'weekday', 'hour', 'minute', 'second',
... ).get(end_datetime__year=ExtractYear('start_datetime'))
{'year': 2015, 'isoyear': 2015, 'quarter': 2, 'month': 6, 'week': 25,
'day': 15, 'weekday': 2, 'hour': 23, 'minute': 30, 'second': 1}
When :setting:`USE_TZ` is ``True`` then datetimes are stored in the database
in UTC. If a different timezone is active in Django, the datetime is converted
to that timezone before the value is extracted. The example below converts to
the Melbourne timezone (UTC +10:00), which changes the day, weekday, and hour
values that are returned::
>>> import pytz
>>> melb = pytz.timezone('Australia/Melbourne') # UTC+10:00
>>> with timezone.override(melb):
... Experiment.objects.annotate(
... day=ExtractDay('start_datetime'),
... weekday=ExtractWeekDay('start_datetime'),
... hour=ExtractHour('start_datetime'),
... ).values('day', 'weekday', 'hour').get(
... end_datetime__year=ExtractYear('start_datetime'),
... )
{'day': 16, 'weekday': 3, 'hour': 9}
Explicitly passing the timezone to the ``Extract`` function behaves in the same
way, and takes priority over an active timezone::
>>> import pytz
>>> melb = pytz.timezone('Australia/Melbourne')
>>> Experiment.objects.annotate(
... day=ExtractDay('start_datetime', tzinfo=melb),
... weekday=ExtractWeekDay('start_datetime', tzinfo=melb),
... hour=ExtractHour('start_datetime', tzinfo=melb),
... ).values('day', 'weekday', 'hour').get(
... end_datetime__year=ExtractYear('start_datetime'),
... )
{'day': 16, 'weekday': 3, 'hour': 9}
``Now``
-------
.. class:: Now()
Returns the database server's current date and time when the query is executed,
typically using the SQL ``CURRENT_TIMESTAMP``.
Usage example::
>>> from django.db.models.functions import Now
>>> Article.objects.filter(published__lte=Now())
<QuerySet [<Article: How to Django>]>
.. admonition:: PostgreSQL considerations
On PostgreSQL, the SQL ``CURRENT_TIMESTAMP`` returns the time that the
current transaction started. Therefore for cross-database compatibility,
``Now()`` uses ``STATEMENT_TIMESTAMP`` instead. If you need the transaction
timestamp, use :class:`django.contrib.postgres.functions.TransactionNow`.
``Trunc``
---------
.. class:: Trunc(expression, kind, output_field=None, tzinfo=None, **extra)
Truncates a date up to a significant component.
When you only care if something happened in a particular year, hour, or day,
but not the exact second, then ``Trunc`` (and its subclasses) can be useful to
filter or aggregate your data. For example, you can use ``Trunc`` to calculate
the number of sales per day.
``Trunc`` takes a single ``expression``, representing a ``DateField``,
``TimeField``, or ``DateTimeField``, a ``kind`` representing a date or time
part, and an ``output_field`` that's either ``DateTimeField()``,
``TimeField()``, or ``DateField()``. It returns a datetime, date, or time
depending on ``output_field``, with fields up to ``kind`` set to their minimum
value. If ``output_field`` is omitted, it will default to the ``output_field``
of ``expression``. A ``tzinfo`` subclass, usually provided by ``pytz``, can be
passed to truncate a value in a specific timezone.
Given the datetime ``2015-06-15 14:30:50.000321+00:00``, the built-in ``kind``\s
return:
* "year": 2015-01-01 00:00:00+00:00
* "quarter": 2015-04-01 00:00:00+00:00
* "month": 2015-06-01 00:00:00+00:00
* "week": 2015-06-15 00:00:00+00:00
* "day": 2015-06-15 00:00:00+00:00
* "hour": 2015-06-15 14:00:00+00:00
* "minute": 2015-06-15 14:30:00+00:00
* "second": 2015-06-15 14:30:50+00:00
If a different timezone like ``Australia/Melbourne`` is active in Django, then
the datetime is converted to the new timezone before the value is truncated.
The timezone offset for Melbourne in the example date above is +10:00. The
values returned when this timezone is active will be:
* "year": 2015-01-01 00:00:00+11:00
* "quarter": 2015-04-01 00:00:00+10:00
* "month": 2015-06-01 00:00:00+10:00
* "week": 2015-06-16 00:00:00+10:00
* "day": 2015-06-16 00:00:00+10:00
* "hour": 2015-06-16 00:00:00+10:00
* "minute": 2015-06-16 00:30:00+10:00
* "second": 2015-06-16 00:30:50+10:00
The year has an offset of +11:00 because the result transitioned into daylight
saving time.
Each ``kind`` above has a corresponding ``Trunc`` subclass (listed below) that
should typically be used instead of the more verbose equivalent,
e.g. use ``TruncYear(...)`` rather than ``Trunc(..., kind='year')``.
The subclasses are all defined as transforms, but they aren't registered with
any fields, because the obvious lookup names are already reserved by the
``Extract`` subclasses.
Usage example::
>>> from datetime import datetime
>>> from django.db.models import Count, DateTimeField
>>> from django.db.models.functions import Trunc
>>> Experiment.objects.create(start_datetime=datetime(2015, 6, 15, 14, 30, 50, 321))
>>> Experiment.objects.create(start_datetime=datetime(2015, 6, 15, 14, 40, 2, 123))
>>> Experiment.objects.create(start_datetime=datetime(2015, 12, 25, 10, 5, 27, 999))
>>> experiments_per_day = Experiment.objects.annotate(
... start_day=Trunc('start_datetime', 'day', output_field=DateTimeField())
... ).values('start_day').annotate(experiments=Count('id'))
>>> for exp in experiments_per_day:
... print(exp['start_day'], exp['experiments'])
...
2015-06-15 00:00:00 2
2015-12-25 00:00:00 1
>>> experiments = Experiment.objects.annotate(
... start_day=Trunc('start_datetime', 'day', output_field=DateTimeField())
... ).filter(start_day=datetime(2015, 6, 15))
>>> for exp in experiments:
... print(exp.start_datetime)
...
2015-06-15 14:30:50.000321
2015-06-15 14:40:02.000123
``DateField`` truncation
~~~~~~~~~~~~~~~~~~~~~~~~
.. class:: TruncYear(expression, output_field=None, tzinfo=None, **extra)
.. attribute:: kind = 'year'
.. class:: TruncMonth(expression, output_field=None, tzinfo=None, **extra)
.. attribute:: kind = 'month'
.. class:: TruncWeek(expression, output_field=None, tzinfo=None, **extra)
.. versionadded:: 2.1
Truncates to midnight on the Monday of the week.
.. attribute:: kind = 'week'
.. class:: TruncQuarter(expression, output_field=None, tzinfo=None, **extra)
.. attribute:: kind = 'quarter'
These are logically equivalent to ``Trunc('date_field', kind)``. They truncate
all parts of the date up to ``kind`` which allows grouping or filtering dates
with less precision. ``expression`` can have an ``output_field`` of either
``DateField`` or ``DateTimeField``.
Since ``DateField``\s don't have a time component, only ``Trunc`` subclasses
that deal with date-parts can be used with ``DateField``::
>>> from datetime import datetime
>>> from django.db.models import Count
>>> from django.db.models.functions import TruncMonth, TruncYear
>>> from django.utils import timezone
>>> start1 = datetime(2014, 6, 15, 14, 30, 50, 321, tzinfo=timezone.utc)
>>> start2 = datetime(2015, 6, 15, 14, 40, 2, 123, tzinfo=timezone.utc)
>>> start3 = datetime(2015, 12, 31, 17, 5, 27, 999, tzinfo=timezone.utc)
>>> Experiment.objects.create(start_datetime=start1, start_date=start1.date())
>>> Experiment.objects.create(start_datetime=start2, start_date=start2.date())
>>> Experiment.objects.create(start_datetime=start3, start_date=start3.date())
>>> experiments_per_year = Experiment.objects.annotate(
... year=TruncYear('start_date')).values('year').annotate(
... experiments=Count('id'))
>>> for exp in experiments_per_year:
... print(exp['year'], exp['experiments'])
...
2014-01-01 1
2015-01-01 2
>>> import pytz
>>> melb = pytz.timezone('Australia/Melbourne')
>>> experiments_per_month = Experiment.objects.annotate(
... month=TruncMonth('start_datetime', tzinfo=melb)).values('month').annotate(
... experiments=Count('id'))
>>> for exp in experiments_per_month:
... print(exp['month'], exp['experiments'])
...
2015-06-01 00:00:00+10:00 1
2016-01-01 00:00:00+11:00 1
2014-06-01 00:00:00+10:00 1
``DateTimeField`` truncation
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. class:: TruncDate(expression, **extra)
.. attribute:: lookup_name = 'date'
.. attribute:: output_field = DateField()
``TruncDate`` casts ``expression`` to a date rather than using the built-in SQL
truncate function. It's also registered as a transform on ``DateTimeField`` as
``__date``.
.. class:: TruncTime(expression, **extra)
.. attribute:: lookup_name = 'time'
.. attribute:: output_field = TimeField()
``TruncTime`` casts ``expression`` to a time rather than using the built-in SQL
truncate function. It's also registered as a transform on ``DateTimeField`` as
``__time``.
.. class:: TruncDay(expression, output_field=None, tzinfo=None, **extra)
.. attribute:: kind = 'day'
.. class:: TruncHour(expression, output_field=None, tzinfo=None, **extra)
.. attribute:: kind = 'hour'
.. class:: TruncMinute(expression, output_field=None, tzinfo=None, **extra)
.. attribute:: kind = 'minute'
.. class:: TruncSecond(expression, output_field=None, tzinfo=None, **extra)
.. attribute:: kind = 'second'
These are logically equivalent to ``Trunc('datetime_field', kind)``. They
truncate all parts of the date up to ``kind`` and allow grouping or filtering
datetimes with less precision. ``expression`` must have an ``output_field`` of
``DateTimeField``.
Usage example::
>>> from datetime import date, datetime
>>> from django.db.models import Count
>>> from django.db.models.functions import (
... TruncDate, TruncDay, TruncHour, TruncMinute, TruncSecond,
... )
>>> from django.utils import timezone
>>> import pytz
>>> start1 = datetime(2014, 6, 15, 14, 30, 50, 321, tzinfo=timezone.utc)
>>> Experiment.objects.create(start_datetime=start1, start_date=start1.date())
>>> melb = pytz.timezone('Australia/Melbourne')
>>> Experiment.objects.annotate(
... date=TruncDate('start_datetime'),
... day=TruncDay('start_datetime', tzinfo=melb),
... hour=TruncHour('start_datetime', tzinfo=melb),
... minute=TruncMinute('start_datetime'),
... second=TruncSecond('start_datetime'),
... ).values('date', 'day', 'hour', 'minute', 'second').get()
{'date': datetime.date(2014, 6, 15),
'day': datetime.datetime(2014, 6, 16, 0, 0, tzinfo=<DstTzInfo 'Australia/Melbourne' AEST+10:00:00 STD>),
'hour': datetime.datetime(2014, 6, 16, 0, 0, tzinfo=<DstTzInfo 'Australia/Melbourne' AEST+10:00:00 STD>),
'minute': 'minute': datetime.datetime(2014, 6, 15, 14, 30, tzinfo=<UTC>),
'second': datetime.datetime(2014, 6, 15, 14, 30, 50, tzinfo=<UTC>)
}
``TimeField`` truncation
~~~~~~~~~~~~~~~~~~~~~~~~
.. class:: TruncHour(expression, output_field=None, tzinfo=None, **extra)
.. attribute:: kind = 'hour'
.. class:: TruncMinute(expression, output_field=None, tzinfo=None, **extra)
.. attribute:: kind = 'minute'
.. class:: TruncSecond(expression, output_field=None, tzinfo=None, **extra)
.. attribute:: kind = 'second'
These are logically equivalent to ``Trunc('time_field', kind)``. They truncate
all parts of the time up to ``kind`` which allows grouping or filtering times
with less precision. ``expression`` can have an ``output_field`` of either
``TimeField`` or ``DateTimeField``.
Since ``TimeField``\s don't have a date component, only ``Trunc`` subclasses
that deal with time-parts can be used with ``TimeField``::
>>> from datetime import datetime
>>> from django.db.models import Count, TimeField
>>> from django.db.models.functions import TruncHour
>>> from django.utils import timezone
>>> start1 = datetime(2014, 6, 15, 14, 30, 50, 321, tzinfo=timezone.utc)
>>> start2 = datetime(2014, 6, 15, 14, 40, 2, 123, tzinfo=timezone.utc)
>>> start3 = datetime(2015, 12, 31, 17, 5, 27, 999, tzinfo=timezone.utc)
>>> Experiment.objects.create(start_datetime=start1, start_time=start1.time())
>>> Experiment.objects.create(start_datetime=start2, start_time=start2.time())
>>> Experiment.objects.create(start_datetime=start3, start_time=start3.time())
>>> experiments_per_hour = Experiment.objects.annotate(
... hour=TruncHour('start_datetime', output_field=TimeField()),
... ).values('hour').annotate(experiments=Count('id'))
>>> for exp in experiments_per_hour:
... print(exp['hour'], exp['experiments'])
...
14:00:00 2
17:00:00 1
>>> import pytz
>>> melb = pytz.timezone('Australia/Melbourne')
>>> experiments_per_hour = Experiment.objects.annotate(
... hour=TruncHour('start_datetime', tzinfo=melb),
... ).values('hour').annotate(experiments=Count('id'))
>>> for exp in experiments_per_hour:
... print(exp['hour'], exp['experiments'])
...
2014-06-16 00:00:00+10:00 2
2016-01-01 04:00:00+11:00 1
.. _math-functions:
Math Functions
==============
.. versionadded:: 2.2
We'll be using the following model in math function examples::
class Vector(models.Model):
x = models.FloatField()
y = models.FloatField()
``Abs``
-------
.. class:: Abs(expression, **extra)
Returns the absolute value of a numeric field or expression.
Usage example::
>>> from django.db.models.functions import Abs
>>> Vector.objects.create(x=-0.5, y=1.1)
>>> vector = Vector.objects.annotate(x_abs=Abs('x'), y_abs=Abs('y')).get()
>>> vector.x_abs, vector.y_abs
(0.5, 1.1)
It can also be registered as a transform. For example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Abs
>>> FloatField.register_lookup(Abs)
>>> # Get vectors inside the unit cube
>>> vectors = Vector.objects.filter(x__abs__lt=1, y__abs__lt=1)
``ACos``
--------
.. class:: ACos(expression, **extra)
Returns the arccosine of a numeric field or expression. The expression value
must be within the range -1 to 1.
Usage example::
>>> from django.db.models.functions import ACos
>>> Vector.objects.create(x=0.5, y=-0.9)
>>> vector = Vector.objects.annotate(x_acos=ACos('x'), y_acos=ACos('y')).get()
>>> vector.x_acos, vector.y_acos
(1.0471975511965979, 2.6905658417935308)
It can also be registered as a transform. For example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import ACos
>>> FloatField.register_lookup(ACos)
>>> # Get vectors whose arccosine is less than 1
>>> vectors = Vector.objects.filter(x__acos__lt=1, y__acos__lt=1)
``ASin``
--------
.. class:: ASin(expression, **extra)
Returns the arcsine of a numeric field or expression. The expression value must
be in the range -1 to 1.
Usage example::
>>> from django.db.models.functions import ASin
>>> Vector.objects.create(x=0, y=1)
>>> vector = Vector.objects.annotate(x_asin=ASin('x'), y_asin=ASin('y')).get()
>>> vector.x_asin, vector.y_asin
(0.0, 1.5707963267948966)
It can also be registered as a transform. For example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import ASin
>>> FloatField.register_lookup(ASin)
>>> # Get vectors whose arcsine is less than 1
>>> vectors = Vector.objects.filter(x__asin__lt=1, y__asin__lt=1)
``ATan``
--------
.. class:: ATan(expression, **extra)
Returns the arctangent of a numeric field or expression.
Usage example::
>>> from django.db.models.functions import ATan
>>> Vector.objects.create(x=3.12, y=6.987)
>>> vector = Vector.objects.annotate(x_atan=ATan('x'), y_atan=ATan('y')).get()
>>> vector.x_atan, vector.y_atan
(1.2606282660069106, 1.428638798133829)
It can also be registered as a transform. For example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import ATan
>>> FloatField.register_lookup(ATan)
>>> # Get vectors whose arctangent is less than 2
>>> vectors = Vector.objects.filter(x__atan__lt=2, y__atan__lt=2)
``ATan2``
---------
.. class:: ATan2(expression1, expression2, **extra)
Returns the arctangent of ``expression1 / expression2``.
Usage example::
>>> from django.db.models.functions import ATan2
>>> Vector.objects.create(x=2.5, y=1.9)
>>> vector = Vector.objects.annotate(atan2=ATan2('x', 'y')).get()
>>> vector.atan2
0.9209258773829491
``Ceil``
--------
.. class:: Ceil(expression, **extra)
Returns the smallest integer greater than or equal to a numeric field or
expression.
Usage example::
>>> from django.db.models.functions import Ceil
>>> Vector.objects.create(x=3.12, y=7.0)
>>> vector = Vector.objects.annotate(x_ceil=Ceil('x'), y_ceil=Ceil('y')).get()
>>> vector.x_ceil, vector.y_ceil
(4.0, 7.0)
It can also be registered as a transform. For example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Ceil
>>> FloatField.register_lookup(Ceil)
>>> # Get vectors whose ceil is less than 10
>>> vectors = Vector.objects.filter(x__ceil__lt=10, y__ceil__lt=10)
``Cos``
-------
.. class:: Cos(expression, **extra)
Returns the cosine of a numeric field or expression.
Usage example::
>>> from django.db.models.functions import Cos
>>> Vector.objects.create(x=-8.0, y=3.1415926)
>>> vector = Vector.objects.annotate(x_cos=Cos('x'), y_cos=Cos('y')).get()
>>> vector.x_cos, vector.y_cos
(-0.14550003380861354, -0.9999999999999986)
It can also be registered as a transform. For example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Cos
>>> FloatField.register_lookup(Cos)
>>> # Get vectors whose cosine is less than 0.5
>>> vectors = Vector.objects.filter(x__cos__lt=0.5, y__cos__lt=0.5)
``Cot``
-------
.. class:: Cot(expression, **extra)
Returns the cotangent of a numeric field or expression.
Usage example::
>>> from django.db.models.functions import Cot
>>> Vector.objects.create(x=12.0, y=1.0)
>>> vector = Vector.objects.annotate(x_cot=Cot('x'), y_cot=Cot('y')).get()
>>> vector.x_cot, vector.y_cot
(-1.5726734063976826, 0.642092615934331)
It can also be registered as a transform. For example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Cot
>>> FloatField.register_lookup(Cot)
>>> # Get vectors whose cotangent is less than 1
>>> vectors = Vector.objects.filter(x__cot__lt=1, y__cot__lt=1)
``Degrees``
-----------
.. class:: Degrees(expression, **extra)
Converts a numeric field or expression from radians to degrees.
Usage example::
>>> from django.db.models.functions import Degrees
>>> Vector.objects.create(x=-1.57, y=3.14)
>>> vector = Vector.objects.annotate(x_d=Degrees('x'), y_d=Degrees('y')).get()
>>> vector.x_d, vector.y_d
(-89.95437383553924, 179.9087476710785)
It can also be registered as a transform. For example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Degrees
>>> FloatField.register_lookup(Degrees)
>>> # Get vectors whose degrees are less than 360
>>> vectors = Vector.objects.filter(x__degrees__lt=360, y__degrees__lt=360)
``Exp``
-------
.. class:: Exp(expression, **extra)
Returns the value of ``e`` (the natural logarithm base) raised to the power of
a numeric field or expression.
Usage example::
>>> from django.db.models.functions import Exp
>>> Vector.objects.create(x=5.4, y=-2.0)
>>> vector = Vector.objects.annotate(x_exp=Exp('x'), y_exp=Exp('y')).get()
>>> vector.x_exp, vector.y_exp
(221.40641620418717, 0.1353352832366127)
It can also be registered as a transform. For example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Exp
>>> FloatField.register_lookup(Exp)
>>> # Get vectors whose exp() is greater than 10
>>> vectors = Vector.objects.filter(x__exp__gt=10, y__exp__gt=10)
``Floor``
---------
.. class:: Floor(expression, **extra)
Returns the largest integer value not greater than a numeric field or
expression.
Usage example::
>>> from django.db.models.functions import Floor
>>> Vector.objects.create(x=5.4, y=-2.3)
>>> vector = Vector.objects.annotate(x_floor=Floor('x'), y_floor=Floor('y')).get()
>>> vector.x_floor, vector.y_floor
(5.0, -3.0)
It can also be registered as a transform. For example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Floor
>>> FloatField.register_lookup(Floor)
>>> # Get vectors whose floor() is greater than 10
>>> vectors = Vector.objects.filter(x__floor__gt=10, y__floor__gt=10)
``Ln``
------
.. class:: Ln(expression, **extra)
Returns the natural logarithm a numeric field or expression.
Usage example::
>>> from django.db.models.functions import Ln
>>> Vector.objects.create(x=5.4, y=233.0)
>>> vector = Vector.objects.annotate(x_ln=Ln('x'), y_ln=Ln('y')).get()
>>> vector.x_ln, vector.y_ln
(1.6863989535702288, 5.4510384535657)
It can also be registered as a transform. For example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Ln
>>> FloatField.register_lookup(Ln)
>>> # Get vectors whose value greater than e
>>> vectors = Vector.objects.filter(x__ln__gt=1, y__ln__gt=1)
``Log``
-------
.. class:: Log(expression1, expression2, **extra)
Accepts two numeric fields or expressions and returns the logarithm of
the first to base of the second.
Usage example::
>>> from django.db.models.functions import Log
>>> Vector.objects.create(x=2.0, y=4.0)
>>> vector = Vector.objects.annotate(log=Log('x', 'y')).get()
>>> vector.log
2.0
``Mod``
-------
.. class:: Mod(expression1, expression2, **extra)
Accepts two numeric fields or expressions and returns the remainder of
the first divided by the second (modulo operation).
Usage example::
>>> from django.db.models.functions import Mod
>>> Vector.objects.create(x=5.4, y=2.3)
>>> vector = Vector.objects.annotate(mod=Mod('x', 'y')).get()
>>> vector.mod
0.8
``Pi``
------
.. class:: Pi(**extra)
Returns the value of the mathematical constant ``π``.
``Power``
---------
.. class:: Power(expression1, expression2, **extra)
Accepts two numeric fields or expressions and returns the value of the first
raised to the power of the second.
Usage example::
>>> from django.db.models.functions import Power
>>> Vector.objects.create(x=2, y=-2)
>>> vector = Vector.objects.annotate(power=Power('x', 'y')).get()
>>> vector.power
0.25
``Radians``
-----------
.. class:: Radians(expression, **extra)
Converts a numeric field or expression from degrees to radians.
Usage example::
>>> from django.db.models.functions import Radians
>>> Vector.objects.create(x=-90, y=180)
>>> vector = Vector.objects.annotate(x_r=Radians('x'), y_r=Radians('y')).get()
>>> vector.x_r, vector.y_r
(-1.5707963267948966, 3.141592653589793)
It can also be registered as a transform. For example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Radians
>>> FloatField.register_lookup(Radians)
>>> # Get vectors whose radians are less than 1
>>> vectors = Vector.objects.filter(x__radians__lt=1, y__radians__lt=1)
``Round``
---------
.. class:: Round(expression, **extra)
Rounds a numeric field or expression to the nearest integer. Whether half
values are rounded up or down depends on the database.
Usage example::
>>> from django.db.models.functions import Round
>>> Vector.objects.create(x=5.4, y=-2.3)
>>> vector = Vector.objects.annotate(x_r=Round('x'), y_r=Round('y')).get()
>>> vector.x_r, vector.y_r
(5.0, -2.0)
It can also be registered as a transform. For example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Round
>>> FloatField.register_lookup(Round)
>>> # Get vectors whose round() is less than 20
>>> vectors = Vector.objects.filter(x__round__lt=20, y__round__lt=20)
``Sin``
-------
.. class:: Sin(expression, **extra)
Returns the sine of a numeric field or expression.
Usage example::
>>> from django.db.models.functions import Sin
>>> Vector.objects.create(x=5.4, y=-2.3)
>>> vector = Vector.objects.annotate(x_sin=Sin('x'), y_sin=Sin('y')).get()
>>> vector.x_sin, vector.y_sin
(-0.7727644875559871, -0.7457052121767203)
It can also be registered as a transform. For example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Sin
>>> FloatField.register_lookup(Sin)
>>> # Get vectors whose sin() is less than 0
>>> vectors = Vector.objects.filter(x__sin__lt=0, y__sin__lt=0)
``Sqrt``
--------
.. class:: Sqrt(expression, **extra)
Returns the square root of a nonnegative numeric field or expression.
Usage example::
>>> from django.db.models.functions import Sqrt
>>> Vector.objects.create(x=4.0, y=12.0)
>>> vector = Vector.objects.annotate(x_sqrt=Sqrt('x'), y_sqrt=Sqrt('y')).get()
>>> vector.x_sqrt, vector.y_sqrt
(2.0, 3.46410)
It can also be registered as a transform. For example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Sqrt
>>> FloatField.register_lookup(Sqrt)
>>> # Get vectors whose sqrt() is less than 5
>>> vectors = Vector.objects.filter(x__sqrt__lt=5, y__sqrt__lt=5)
``Tan``
-------
.. class:: Tan(expression, **extra)
Returns the tangent of a numeric field or expression.
Usage example::
>>> from django.db.models.functions import Tan
>>> Vector.objects.create(x=0, y=12)
>>> vector = Vector.objects.annotate(x_tan=Tan('x'), y_tan=Tan('y')).get()
>>> vector.x_tan, vector.y_tan
(0.0, -0.6358599286615808)
It can also be registered as a transform. For example::
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Tan
>>> FloatField.register_lookup(Tan)
>>> # Get vectors whose tangent is less than 0
>>> vectors = Vector.objects.filter(x__tan__lt=0, y__tan__lt=0)
.. _text-functions:
Text functions
==============
``Chr``
-------
.. class:: Chr(expression, **extra)
.. versionadded:: 2.1
Accepts a numeric field or expression and returns the text representation of
the expression as a single character. It works the same as Python's :func:`chr`
function.
Like :class:`Length`, it can be registered as a transform on ``IntegerField``.
The default lookup name is ``chr``.
Usage example::
>>> from django.db.models.functions import Chr
>>> Author.objects.create(name='Margaret Smith')
>>> author = Author.objects.filter(name__startswith=Chr(ord('M'))).get()
>>> print(author.name)
Margaret Smith
``Concat``
----------
.. class:: Concat(*expressions, **extra)
Accepts a list of at least two text fields or expressions and returns the
concatenated text. Each argument must be of a text or char type. If you want
to concatenate a ``TextField()`` with a ``CharField()``, then be sure to tell
Django that the ``output_field`` should be a ``TextField()``. Specifying an
``output_field`` is also required when concatenating a ``Value`` as in the
example below.
This function will never have a null result. On backends where a null argument
results in the entire expression being null, Django will ensure that each null
part is converted to an empty string first.
Usage example::
>>> # Get the display name as "name (goes_by)"
>>> from django.db.models import CharField, Value as V
>>> from django.db.models.functions import Concat
>>> Author.objects.create(name='Margaret Smith', goes_by='Maggie')
>>> author = Author.objects.annotate(
... screen_name=Concat(
... 'name', V(' ('), 'goes_by', V(')'),
... output_field=CharField()
... )
... ).get()
>>> print(author.screen_name)
Margaret Smith (Maggie)
``Left``
--------
.. class:: Left(expression, length, **extra)
.. versionadded:: 2.1
Returns the first ``length`` characters of the given text field or expression.
Usage example::
>>> from django.db.models.functions import Left
>>> Author.objects.create(name='Margaret Smith')
>>> author = Author.objects.annotate(first_initial=Left('name', 1)).get()
>>> print(author.first_initial)
M
``Length``
----------
.. class:: Length(expression, **extra)
Accepts a single text field or expression and returns the number of characters
the value has. If the expression is null, then the length will also be null.
Usage example::
>>> # Get the length of the name and goes_by fields
>>> from django.db.models.functions import Length
>>> Author.objects.create(name='Margaret Smith')
>>> author = Author.objects.annotate(
... name_length=Length('name'),
... goes_by_length=Length('goes_by')).get()
>>> print(author.name_length, author.goes_by_length)
(14, None)
It can also be registered as a transform. For example::
>>> from django.db.models import CharField
>>> from django.db.models.functions import Length
>>> CharField.register_lookup(Length)
>>> # Get authors whose name is longer than 7 characters
>>> authors = Author.objects.filter(name__length__gt=7)
``Lower``
---------
.. class:: Lower(expression, **extra)
Accepts a single text field or expression and returns the lowercase
representation.
It can also be registered as a transform as described in :class:`Length`.
Usage example::
>>> from django.db.models.functions import Lower
>>> Author.objects.create(name='Margaret Smith')
>>> author = Author.objects.annotate(name_lower=Lower('name')).get()
>>> print(author.name_lower)
margaret smith
``LPad``
--------
.. class:: LPad(expression, length, fill_text=Value(' '), **extra)
.. versionadded:: 2.1
Returns the value of the given text field or expression padded on the left side
with ``fill_text`` so that the resulting value is ``length`` characters long.
The default ``fill_text`` is a space.
Usage example::
>>> from django.db.models import Value
>>> from django.db.models.functions import LPad
>>> Author.objects.create(name='John', alias='j')
>>> Author.objects.update(name=LPad('name', 8, Value('abc')))
1
>>> print(Author.objects.get(alias='j').name)
abcaJohn
``LTrim``
---------
.. class:: LTrim(expression, **extra)
.. versionadded:: 2.1
Similar to :class:`~django.db.models.functions.Trim`, but removes only leading
spaces.
``Ord``
-------
.. class:: Ord(expression, **extra)
.. versionadded:: 2.1
Accepts a single text field or expression and returns the Unicode code point
value for the first character of that expression. It works similar to Python's
:func:`ord` function, but an exception isn't raised if the expression is more
than one character long.
It can also be registered as a transform as described in :class:`Length`.
The default lookup name is ``ord``.
Usage example::
>>> from django.db.models.functions import Ord
>>> Author.objects.create(name='Margaret Smith')
>>> author = Author.objects.annotate(name_code_point=Ord('name')).get()
>>> print(author.name_code_point)
77
``Repeat``
----------
.. class:: Repeat(expression, number, **extra)
.. versionadded:: 2.1
Returns the value of the given text field or expression repeated ``number``
times.
Usage example::
>>> from django.db.models.functions import Repeat
>>> Author.objects.create(name='John', alias='j')
>>> Author.objects.update(name=Repeat('name', 3))
1
>>> print(Author.objects.get(alias='j').name)
JohnJohnJohn
``Replace``
-----------
.. class:: Replace(expression, text, replacement=Value(''), **extra)
.. versionadded:: 2.1
Replaces all occurrences of ``text`` with ``replacement`` in ``expression``.
The default replacement text is the empty string. The arguments to the function
are case-sensitive.
Usage example::
>>> from django.db.models import Value
>>> from django.db.models.functions import Replace
>>> Author.objects.create(name='Margaret Johnson')
>>> Author.objects.create(name='Margaret Smith')
>>> Author.objects.update(name=Replace('name', Value('Margaret'), Value('Margareth')))
2
>>> Author.objects.values('name')
<QuerySet [{'name': 'Margareth Johnson'}, {'name': 'Margareth Smith'}]>
``Right``
---------
.. class:: Right(expression, length, **extra)
.. versionadded:: 2.1
Returns the last ``length`` characters of the given text field or expression.
Usage example::
>>> from django.db.models.functions import Right
>>> Author.objects.create(name='Margaret Smith')
>>> author = Author.objects.annotate(last_letter=Right('name', 1)).get()
>>> print(author.last_letter)
h
``RPad``
--------
.. class:: RPad(expression, length, fill_text=Value(' '), **extra)
.. versionadded:: 2.1
Similar to :class:`~django.db.models.functions.LPad`, but pads on the right
side.
``RTrim``
---------
.. class:: RTrim(expression, **extra)
.. versionadded:: 2.1
Similar to :class:`~django.db.models.functions.Trim`, but removes only trailing
spaces.
``StrIndex``
------------
.. class:: StrIndex(string, substring, **extra)
Returns a positive integer corresponding to the 1-indexed position of the first
occurrence of ``substring`` inside ``string``, or 0 if ``substring`` is not
found.
Usage example::
>>> from django.db.models import Value as V
>>> from django.db.models.functions import StrIndex
>>> Author.objects.create(name='Margaret Smith')
>>> Author.objects.create(name='Smith, Margaret')
>>> Author.objects.create(name='Margaret Jackson')
>>> Author.objects.filter(name='Margaret Jackson').annotate(
... smith_index=StrIndex('name', V('Smith'))
... ).get().smith_index
0
>>> authors = Author.objects.annotate(
... smith_index=StrIndex('name', V('Smith'))
... ).filter(smith_index__gt=0)
<QuerySet [<Author: Margaret Smith>, <Author: Smith, Margaret>]>
.. warning::
In MySQL, a database table's :ref:`collation<mysql-collation>` determines
whether string comparisons (such as the ``expression`` and ``substring`` of
this function) are case-sensitive. Comparisons are case-insensitive by
default.
``Substr``
----------
.. class:: Substr(expression, pos, length=None, **extra)
Returns a substring of length ``length`` from the field or expression starting
at position ``pos``. The position is 1-indexed, so the position must be greater
than 0. If ``length`` is ``None``, then the rest of the string will be returned.
Usage example::
>>> # Set the alias to the first 5 characters of the name as lowercase
>>> from django.db.models.functions import Lower, Substr
>>> Author.objects.create(name='Margaret Smith')
>>> Author.objects.update(alias=Lower(Substr('name', 1, 5)))
1
>>> print(Author.objects.get(name='Margaret Smith').alias)
marga
``Trim``
--------
.. class:: Trim(expression, **extra)
.. versionadded:: 2.1
Returns the value of the given text field or expression with leading and
trailing spaces removed.
Usage example::
>>> from django.db.models.functions import Trim
>>> Author.objects.create(name=' John ', alias='j')
>>> Author.objects.update(name=Trim('name'))
1
>>> print(Author.objects.get(alias='j').name)
John
``Upper``
---------
.. class:: Upper(expression, **extra)
Accepts a single text field or expression and returns the uppercase
representation.
It can also be registered as a transform as described in :class:`Length`.
Usage example::
>>> from django.db.models.functions import Upper
>>> Author.objects.create(name='Margaret Smith')
>>> author = Author.objects.annotate(name_upper=Upper('name')).get()
>>> print(author.name_upper)
MARGARET SMITH
.. _window-functions:
Window functions
================
There are a number of functions to use in a
:class:`~django.db.models.expressions.Window` expression for computing the rank
of elements or the :class:`Ntile` of some rows.
``CumeDist``
------------
.. class:: CumeDist(*expressions, **extra)
Calculates the cumulative distribution of a value within a window or partition.
The cumulative distribution is defined as the number of rows preceding or
peered with the current row divided by the total number of rows in the frame.
``DenseRank``
-------------
.. class:: DenseRank(*expressions, **extra)
Equivalent to :class:`Rank` but does not have gaps.
``FirstValue``
--------------
.. class:: FirstValue(expression, **extra)
Returns the value evaluated at the row that's the first row of the window
frame, or ``None`` if no such value exists.
``Lag``
-------
.. class:: Lag(expression, offset=1, default=None, **extra)
Calculates the value offset by ``offset``, and if no row exists there, returns
``default``.
``default`` must have the same type as the ``expression``, however, this is
only validated by the database and not in Python.
.. admonition:: MariaDB and ``default``
MariaDB `doesn't support <https://jira.mariadb.org/browse/MDEV-12981>`_
the ``default`` parameter.
``LastValue``
-------------
.. class:: LastValue(expression, **extra)
Comparable to :class:`FirstValue`, it calculates the last value in a given
frame clause.
``Lead``
--------
.. class:: Lead(expression, offset=1, default=None, **extra)
Calculates the leading value in a given :ref:`frame <window-frames>`. Both
``offset`` and ``default`` are evaluated with respect to the current row.
``default`` must have the same type as the ``expression``, however, this is
only validated by the database and not in Python.
.. admonition:: MariaDB and ``default``
MariaDB `doesn't support <https://jira.mariadb.org/browse/MDEV-12981>`_
the ``default`` parameter.
``NthValue``
------------
.. class:: NthValue(expression, nth=1, **extra)
Computes the row relative to the offset ``nth`` (must be a positive value)
within the window. Returns ``None`` if no row exists.
Some databases may handle a nonexistent nth-value differently. For example,
Oracle returns an empty string rather than ``None`` for character-based
expressions. Django doesn't do any conversions in these cases.
``Ntile``
---------
.. class:: Ntile(num_buckets=1, **extra)
Calculates a partition for each of the rows in the frame clause, distributing
numbers as evenly as possible between 1 and ``num_buckets``. If the rows don't
divide evenly into a number of buckets, one or more buckets will be represented
more frequently.
``PercentRank``
---------------
.. class:: PercentRank(*expressions, **extra)
Computes the percentile rank of the rows in the frame clause. This
computation is equivalent to evaluating::
(rank - 1) / (total rows - 1)
The following table explains the calculation for the percentile rank of a row:
===== ===== ==== ============ ============
Row # Value Rank Calculation Percent Rank
===== ===== ==== ============ ============
1 15 1 (1-1)/(7-1) 0.0000
2 20 2 (2-1)/(7-1) 0.1666
3 20 2 (2-1)/(7-1) 0.1666
4 20 2 (2-1)/(7-1) 0.1666
5 30 5 (5-1)/(7-1) 0.6666
6 30 5 (5-1)/(7-1) 0.6666
7 40 7 (7-1)/(7-1) 1.0000
===== ===== ==== ============ ============
``Rank``
--------
.. class:: Rank(*expressions, **extra)
Comparable to ``RowNumber``, this function ranks rows in the window. The
computed rank contains gaps. Use :class:`DenseRank` to compute rank without
gaps.
``RowNumber``
-------------
.. class:: RowNumber(*expressions, **extra)
Computes the row number according to the ordering of either the frame clause
or the ordering of the whole query if there is no partitioning of the
:ref:`window frame <window-frames>`.
Reference in New Issue View Git Blame Copy Permalink